WIRELESS SENSOR NETWORKS TO IMPROVE ENERGY EFFICIENCY IN DATA CENTERS

2021 ◽  
pp. 163-174
Author(s):  
Levente Klein ◽  
Sergio Bermudez ◽  
Fernando Marianno ◽  
Hendrik Hamann
2014 ◽  
Vol 666 ◽  
pp. 322-326
Author(s):  
Yu Yang Peng ◽  
Jae Ho Choi

Energy efficiency is one of the important hot issues in wireless sensor networks. In this paper, a multi-hop scheme based on a cooperative multi-input multi-outputspatial modulation technique is proposed in order to improve energy efficiency in WSN. In this scheme, the sensor nodes are grouped into clusters in order to achieve a multi-input multi-output system; and a simple forwarding transmission scenario is considered so that the intermediate clusters only forward packets originated from the source cluster down to the sink cluster. In order to verify the performance of the proposed system, the bit energy consumption formula is derived and the optimal number of hopsis determined. By qualitative experiments, the obtained results show that the proposed scheme can deliver the data over multiple hops consuming optimal energy consumption per bit.


2020 ◽  
Vol 16 (1) ◽  
pp. 66-74
Author(s):  
René Bergelt ◽  
Wolfram Hardt

Wireless sensor networks (WSN) are deployed in a multitude of applications both in industrial and academic fields. In recent years, due to the emerge of Internet of Things (IoT) technologies and Vehicle2X communication scenarios, novel challenges for wireless sensor network platforms - regarding hardware and software - arose. Thus, challenges known from big data processing have reached the WSN scope and consequently approaches and methods have been devised to handle these. One such approach is queriable wireless sensor networks which enable their users the specification of sensing tasks in a declarative way without the need to re-program nodes in case the application requirements change. As many current WSN applications feature active parts with which nodes can directly influence their environment, the term wireless sensor actuator networks (WSAN) has been coined, setting such networks apart from solely passively measuring networks.In this article, we will present a short introduction to big data processing in wireless sensor networks which motivates the usage of queriable networks. We will show that in order to enable a WSAN to carry out actions energy-efficiently and in a timely manner, an event-based action model is favorable. Additionally, we will demonstrate how such an event system can be used to improve sub query performance in WSNs. We conclude with an evaluation regarding the benefit of combining this approach with wake-up receiver technologies based on a qualitative energy efficiency definition for WSN.


Author(s):  
Sangsoon Lim

<span>In battery-based wireless sensor networks, energy-efficient operation is one of the most important factors. Especially, in order to improve energy efficiency in wireless sensor networks, various studies on low power operation have been actively conducted in the MAC layer. In recent years, mutual interference among various radio technologies using the same radio frequency band has become a serious problem. Wi-Fi, ZigBee, and Bluetooth use the same frequency band of 2.4GHz at the same time, which causes various signal interference problems. In this paper, we propose a novel channel reservation scheme, called IACR, to improve the energy efficiency of wireless sensor networks in an environment where interference occurs between various wireless technologies. The proposed scheme inserts a PN code into a long preamble for exchanging transmission status information between a transmitting node and a receiving node, thereby improving the transmission success probability while receiving less influence on transmission of other radio technologies. We performed an event-driven simulation and an experiment to measure the signal detection rate. As a result, it can be seen that the proposed technique reduces the packet drop rate by 15% and increases the discoverable distance of the control packet for channel reservation.</span>


2016 ◽  
Vol 850 ◽  
pp. 23-29
Author(s):  
Wen Zhi Zhu ◽  
Feng Xu

In wireless sensor networks, clustering class routing protocol is an important protocol type. Different clustering methods, and cluster head selection method directly affects the energy consumption of the entire network communication. This paper studies the effect of different partition methods of the network energy consumption, and to study the partitioning methods under the conditions of uneven distribution of nodes. We believe that energy efficiency clustering method should adapt the distributed of sensor nodes in order to improve energy efficiency. And according to the partition method we propose a low-power adaptive clustering routing protocol based on node distribution to partition. The protocol can effectively extend the lifetime of a wireless sensor network. Simulation results show that the proposed protocol can effectively prolong the network lifetime.


2011 ◽  
Vol 7 (2) ◽  
pp. 130-137
Author(s):  
Ghaida AL-Suhail

In this paper, we develop an analytical energy efficiency model using dual switched branch diversity receiver in wireless sensor networks in fading environments. To adapt energy efficiency of sensor node to channel variations, the optimal packet length at the data link layer is considered. Within this model, the energy efficiency can be effectively improved for switch-and-stay combiner (SSC) receiver with optimal switching threshold. Moreover, to improve energy efficiency, we use error control of Bose-Chaudhuri-Hochquengh (BCH) coding for SSC-BPSK receiver node compared to one of non-diversity NCFSK receiver of sensor node. The results show that the BCH code for channel coding can improve the energy efficiency significantly for long link distance and various values of high energy consumptions over Rayleigh fading channel.


Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2654 ◽  
Author(s):  
Yuan Rao ◽  
Gang Zhao ◽  
Wen Wang ◽  
Jingyao Zhang ◽  
Zhaohui Jiang ◽  
...  

Due to the limited energy budget, great efforts have been made to improve energy efficiency for wireless sensor networks. The advantage of compressed sensing is that it saves energy because of its sparse sampling; however, it suffers inherent shortcomings in relation to timely data acquisition. In contrast, prediction-based approaches are able to offer timely data acquisition, but the overhead of frequent model synchronization and data sampling weakens the gain in the data reduction. The integration of compressed sensing and prediction-based approaches is one promising data acquisition scheme for the suppression of data transmission, as well as timely collection of critical data, but it is challenging to adaptively and effectively conduct appropriate switching between the two aforementioned data gathering modes. Taking into account the characteristics of data gathering modes and monitored data, this research focuses on several key issues, such as integration framework, adaptive deviation tolerance, and adaptive switching mechanism of data gathering modes. In particular, the adaptive deviation tolerance is proposed for improving the flexibility of data acquisition scheme. The adaptive switching mechanism aims at overcoming the drawbacks in the traditional method that fails to effectively react to the phenomena change unless the sampling frequency is sufficiently high. Through experiments, it is demonstrated that the proposed scheme has good flexibility and scalability, and is capable of simultaneously achieving good energy efficiency and high-quality sensing of critical events.


Sign in / Sign up

Export Citation Format

Share Document